Simplifications in the Optimization of Heat Pumps and Their Comparison for Effects on the Accuracy of the Results

This work presents a model that calculates temperature-dependent heat pump performances as a circular heat pump process as a reference model. The model is then systematically simplified by making assumptions or applying functional approximations to key variables. These simplifications include linearization of the substance database calculations and modeling of the compressor efficiency as a function or constant. The effects of these simplifications on the accuracy of results are quantified and compared with other modeling approaches from the literature suitable for linear and bilinear optimization issues. Initial comparisons show that the root mean square error of the model achieves better results than comparable methods. While the root mean square error of the COP in linearized models in the compared literature ranges from 0.433 to 1.233, it can be improved to a maximum of 0.335 using the approach presented.

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Publication Details

Journal
Energies
Published
2026-01-26
DOI
https://doi.org/10.3390/en19030635
Primary Topic
Refrigeration and Air Conditioning Technologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Simplifications in the Optimization of Heat Pumps and Their Comparison for Effects on the Accuracy of the Results

F. Alsmeyer, Maurice Görgen, Louisa Zaubitzer
Energies
Refrigeration and Air Conditioning Technologies
article

Simplifications in the Optimization of Heat Pumps and Their Comparison for Effects on the Accuracy of the Results

F. Alsmeyer, Maurice Görgen, Louisa Zaubitzer
article en

Abstract

This work presents a model that calculates temperature-dependent heat pump performances as a circular heat pump process as a reference model. The model is then systematically simplified by making assumptions or applying functional approximations to key variables. These simplifications include linearization of the substance database calculations and modeling of the compressor efficiency as a function or constant. The effects of these simplifications on the accuracy of results are quantified and compared with other modeling approaches from the literature suitable for linear and bilinear optimization issues. Initial comparisons show that the root mean square error of the model achieves better results than comparable methods. While the root mean square error of the COP in linearized models in the compared literature ranges from 0.433 to 1.233, it can be improved to a maximum of 0.335 using the approach presented.

EnergiesVol. 19(3)
Hochschule Niederrhein (DE)
Openalex Percentile: Top 77%
Refrigeration and Air Conditioning Technologies
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